Abstract

The optimization of multiple responses (or performance characteristics) has received increasing attention over the last few years in many manufacturing organizations. Many Taguchi practitioners have employed past experience and engineering knowledge or judgement when dealing with multiple responses. This approach brings an element of uncertainty to the decision-making process and therefore is not recommended for optimization of multiple responses. The approach presented in this paper takes advantage of both the Taguchi method and a fuzzy-rule based inference system, which forms a robust and practical methodology in tackling multiple response optimization problems. The paper also presents a case study to illustrate the potential of this powerful integrated approach for tackling multiple response optimization problems. The variance analysis is also an integral part of the study, which identifies the most critical and statistically significant parameters.